DP-200 Azure Data Processing and Pipelines 2 — Questions and Answers
Question 1: In Azure Databricks, what is a Delta Lake table?
- A proprietary binary format incompatible with Spark
- An ACID-compliant storage layer built on Parquet files with a transaction log (Correct answer)
- A real-time streaming sink only
- A NoSQL document store
Correct answer: An ACID-compliant storage layer built on Parquet files with a transaction log
Delta Lake adds ACID transactions, schema enforcement, and time travel to Parquet files by maintaining a JSON transaction log alongside the data.
Question 2: What Azure Databricks feature allows you to query the state of a Delta table at a previous point in time?
- Schema evolution
- Time travel (Correct answer)
- Z-ordering
- Auto Loader
Correct answer: Time travel
Delta Lake time travel allows querying historical table versions using VERSION AS OF or TIMESTAMP AS OF syntax.
Question 3: In Azure Databricks, which command is used to optimize a Delta table by compacting small files into larger ones?
- VACUUM
- ANALYZE
- OPTIMIZE (Correct answer)
- COMPACT
Correct answer: OPTIMIZE
The OPTIMIZE command in Delta Lake compacts small Parquet files into larger ones, improving query performance by reducing file overhead.
Question 4: What does the VACUUM command do on a Delta Lake table?
- Compacts small files into larger Parquet files
- Removes old data files no longer referenced by the transaction log (Correct answer)
- Rebuilds statistics for query optimization
- Applies schema changes to all partitions
Correct answer: Removes old data files no longer referenced by the transaction log
VACUUM deletes data files older than the retention threshold that are no longer referenced by the Delta transaction log, reclaiming storage.
Question 5: Which Azure service is used to ingest high-velocity streaming data such as telemetry from millions of IoT devices before processing in Azure Databricks?
- Azure Service Bus
- Azure Event Hubs (Correct answer)
- Azure Notification Hubs
- Azure Relay
Correct answer: Azure Event Hubs
Azure Event Hubs is a massively scalable event streaming platform that can ingest millions of events per second for downstream processing.
Question 6: What is the primary benefit of using Azure Data Factory's data flow (mapping data flow) over a custom Spark script?
- Lower memory usage
- Codeless, visually designed transformations that run on Spark clusters (Correct answer)
- Faster execution than hand-written Spark code
- Support for real-time streaming only
Correct answer: Codeless, visually designed transformations that run on Spark clusters
Mapping data flows provide a visual, codeless interface for building Spark transformations, making complex ETL accessible without Spark expertise.
DP-200 Azure Data Processing and Pipelines 2
In Azure Databricks, what is a Delta Lake table?